Free Amazon Sales Estimator
Free Amazon Sales Estimator
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Estimate monthly and daily unit sales from category and BSR. Compare demand across products fast. Make smarter sourcing and listing decisions.
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Scrape Amazon Data with AIUse Thunderbit’s Chrome extension to scrape listings and extract structured product data fast. Automate collection from pages, subpages, and files without coding.
Install fromChrome Web Store
Scrape Amazon Data with AI
Scraping Amazon and other sites for product research takes time when you copy, paste, and clean data by hand. Thunderbit scrapes websites, follows subpages, and extracts structured fields like title, price, BSR, ratings, and seller details, plus data from PDFs, docs, and images.
Use AI Suggest Fields to set up columns in clicks, then summarize, categorize, and format the results as you scrape. Export to Google Sheets, Airtable, or Notion to track competitors, validate demand, and keep your dataset up to date.
How to Estimate Amazon Sales Using Thunderbit
STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
STEP 2Open ExtensionOpen the Thunderbit Chrome Extension, then select the Free Amazon Sales Estimator. In the "Estimate Amazon Sales" tab, choose a Product Category from the dropdown (this sets the context for interpreting BSR). Next, enter the Best Seller Rank (BSR) as a whole number with no commas (for example, 12500).
STEP 3Click the Estimate sales ButtonClick the "Estimate sales" button to generate results. Thunderbit will validate that the BSR is a positive integer, then return a table with two outputs: "Estimated Monthly Sales (Units)" and "Estimated Daily Sales (Units)". Export the table to Excel, Google Sheets, Airtable, or Notion, or download it as CSV or JSON.
Learn how to estimate Amazon product sales from BSR and category
Estimate sales from Best Seller Rank
Use the Free Amazon Sales Estimator to turn a product’s Best Seller Rank into practical sales volume estimates. Choose the relevant Amazon category, enter the BSR as a whole number, and get estimated monthly and daily unit sales. This helps ecommerce operators, brand managers, and product researchers size demand without building spreadsheets or hunting for benchmarks across multiple sources.
Validate inputs and return consistent unit counts
The tool checks that the BSR is a positive integer before calculating results. If the input is invalid, it returns null values to prevent bad assumptions from entering your workflow. When valid, it outputs numeric unit counts for both monthly and daily sales, with daily aligned to monthly using a 30-day approximation and rounded to whole units for planning, forecasting, and comparisons.
Prioritize products for sourcing and launches
Use the estimates to compare multiple ASINs and decide which products deserve deeper research. Sourcing teams can gauge whether a niche has enough velocity, while private label sellers can sanity-check demand before investing in inventory, packaging, and ads. It is also useful for evaluating variations within a category, such as size, color, or bundle options, using their BSR values.
Support pricing, inventory, and competitor monitoring
Pair the estimator with Thunderbit’s AI Web Scraper to collect BSR and product details from listings, then estimate sales to guide inventory targets and reorder timing. Ecommerce teams can track competitors over time, spot rising products, and map rank changes to expected unit movement. The output is structured for easy analysis in spreadsheets or databases alongside price, reviews, and seller data.
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What users say about Thunderbit
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Frequently Asked Questions
Extract Data using AI
Easily transfer data to Google Sheets, Airtable, or Notion
Chrome Store Rating
PRODUCT HUNT#1 Product of the Week